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高校专区

Northeastern University(东北大学)

2026-03-13 至 2026-03-13 共收录 4
2603.11802 2026-03-13 cs.AI

A Semi-Decentralized Approach to Multiagent Control

多智能体控制的半去中心化方法

Mahdi Al-Husseini, Mykel J. Kochenderfer, Kyle H. Wray

机构 * Stanford University(斯坦福大学) Northeastern University(东北大学)

AI总结 本文提出半去中心化方法,用于解决多智能体控制中的通信不确定性问题,通过SDec-POMDP框架统一了去中心化和多智能体POMDP,并引入RS-SDA*算法生成最优策略。

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2603.11658 2026-03-13 cs.RO

Coupling Tensor Trains with Graph of Convex Sets: Effective Compression, Exploration, and Planning in the C-Space

张量张量与凸集图的耦合:在C空间中实现有效的压缩、探索与规划

Gerhard Reinerth, Riddhiman Laha, Marcello Romano

机构 * Technical University of Munich(慕尼黑技术大学) Northeastern University(东北大学)

AI总结 TANGO通过结合张量压缩与图优化,在C空间中实现高效、几何感知的运动规划,提升轨迹生成的质量和效率。

Comments 8 pages, 10 figures, accepted paper for ICRA2026

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2603.11644 2026-03-13 cs.CV cs.AI

IDRL: An Individual-Aware Multimodal Depression-Related Representation Learning Framework for Depression Diagnosis

IDRL: 一种面向抑郁症诊断的个体感知多模态抑郁症相关表示学习框架

Chongxiao Wang, Junjie Liang, Peng Cao, Jinzhu Yang, Osmar R. Zaiane

机构 * School of Computer Science and Engineering, Northeastern University, Shenyang, China(东北大学计算机科学与工程学院) Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education, Northeastern University, Shenyang, China(教育部医学图像智能计算重点实验室) National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang, China(工业智能与系统优化国家级前沿科学中心) Alberta Machine Intelligence Institute, University of Alberta, Edmonton, Canada(阿尔伯塔机器智能研究所,阿尔伯塔大学,加拿大爱德蒙顿)

AI总结 IDRL框架通过分解多模态表示并引入个体感知的模态融合模块,提升抑郁症诊断的鲁棒性和适应性。

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2603.11125 2026-03-13 stat.ML cs.LG

Co-Diffusion: An Affinity-Aware Two-Stage Latent Diffusion Framework for Generalizable Drug-Target Affinity Prediction

Co-Diffusion:一种面向亲和力的两阶段潜在扩散框架用于通用化药物-靶点亲和力预测

Yining Qian, Pengjie Wang, Yixiao Li, An-Yang Lu, Cheng Tan, Shuang Li, Lijun Liu

机构 * School of Computer Science and Engineering, Northeastern University(东北大学计算机科学与工程学院) College of Information Science and Engineering, Northeastern University(东北大学信息科学与工程学院) Westlake University(西湖大学) School of Artificial Intelligence, Beihang University(北航人工智能学院) Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University(辽宁省生物资源研究开发重点实验室,东北大学生命与健康科学学院)

AI总结 Co-Diffusion通过两阶段潜在扩散框架提升药物-靶点亲和力预测的泛化能力,解决冷启动问题并增强零样本泛化。

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